How to Rank in AI Overviews

The short answer, and why people dislike it

There is no separate ranking system for AI Overviews. The generated summary at the top of a Google Search results page is written by a customized Gemini model working alongside the ranking systems Google already had, and it draws on the same index that produces the ordinary results underneath it. Google's documentation on AI features, last updated 10 December 2025, puts it in one sentence: "There are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary." The same page adds that "You don't need to create new machine readable files, AI text files, or markup to appear in these features." Gary Illyes said the same thing at Google's Search Central Deep Dive in Asia-Pacific in July 2025, as relayed by Kenichi Suzuki and reported by Barry Schwartz: use normal SEO practices, and you do not need generative engine optimization, LLM optimization or anything else.

That is the whole of the documented answer, and it is why this page carries fewer instructions than most pages with this title and why its verdict is Observed rather than Documented. Google documents the gate. Nobody documents how the cited pages are chosen from the far larger set that clears it. What follows says what genuinely proceeds from that architecture, and where the evidence runs out.

What Google's statement means, and what it does not

"No additional requirements" is a claim about interfaces. It says there is no submission form, no registration, no markup channel and no separate index for generative answers. Read that way it is straightforwardly true, and easy to verify: no operator has ever shipped a mechanism for putting a page into an AI answer.

It is routinely read as a stronger claim — that ranking well for a query determines whether you are cited in the answer to that query. Google has never said this. It has never denied it either. The two sentences do different work, and collapsing them is the commonest reading error in the subject.

The distinction matters because the evidence on the stronger claim has moved fast. If most cited pages no longer rank for the visible query, then "do ordinary SEO for the query you want" is an incomplete description of what produces a citation, even while it remains the only reliable lever a publisher has. Google's position is best read as we have not built you a separate channel — not as a promise that ranking and citation track each other.

The one documented requirement is eligibility

Google states one checkable rule: "To be eligible to be shown as a supporting link in AI Overviews or AI Mode, a page must be indexed and eligible to be shown in Google Search with a snippet, fulfilling the Search technical requirements." Read it for what it lacks. There is no quality language in it, no authorship, no schema, no freshness, no word count. The quality judgment happens upstream in ordinary ranking, because the grounding corpus is the ordinary index.

Two consequences follow, and both tend to surface by accident in a technical audit rather than by design. The first is that snippet controls bite: because eligibility requires snippet eligibility, nosnippet, data-nosnippet, max-snippet and noindex all curtail AI Overview eligibility as a side effect of what they were deployed to do. A site that added nosnippet years ago for reasons nobody now remembers has opted out of something that did not then exist.

The second is that the robots.txt token most often used as an AI opt-out does not touch this surface. Google-Extended governs training and grounding for Gemini apps and Vertex AI, and Google states it "does not impact a site's inclusion in Google Search nor is it used as a ranking signal in Google Search." AI Overviews are a Google Search feature. The control that governs them is the search generative AI control in Search Console, live since 17 June 2026, which Google says "isn't used as a ranking or inclusion signal affecting other parts of Search" — so it removes you from the generative features without costing ordinary results. Publishers who blocked Google-Extended believing they had left AI Overviews left Gemini grounding instead and stayed exactly where they were. The documentation is at Google's AI features and your website page.

Query fan-out has weakened the link between ranking and citation

Query fan-out — Google's own term for issuing multiple related searches across subtopics and data sources before an answer is written — is documented in Search Central, and it complicates everything above. Robby Stein, a vice president of product for Search, described it less formally as the system thinking of a bunch of questions and starting to Google them, and later as "maybe dozens of queries." Google publishes no count, no list of sub-queries for any prompt and no weighting, and nothing in Search Console exposes them.

The measured consequence is the most important number on this page, and it has a short shelf life. In July 2025 Ahrefs examined 1.9 million citations from 1 million AI Overviews and found 76.10% of cited pages ranked in the top ten for the query being answered. In March 2026 the same authors re-ran it across 863,000 keyword SERPs and roughly 4 million AI Overview URLs and found 37.9% in the top ten, 31.2% at positions 11 to 100, and 31.0% outside the top 100. Their reading is that Gemini 3, the default model for AI Overviews since 27 January 2026, leans harder on fan-out.

Treat the direction as real and the exact delta as soft: one vendor, one index, and Ahrefs discloses that it improved its citation parsing between the two studies, so part of the movement is measurement rather than behavior. Quote it with its date attached. Ahrefs' own evergreen guide still carried the superseded 76% figure on 12 August 2026, seven months after Ahrefs retired it — as clean an illustration as the field offers of a stale number outliving the study that killed it. The follow-up is at Ahrefs' March 2026 citation analysis.

The tactics the evidence does not support

This is where money changes hands for work with nothing behind it, so each item is worth naming along with where the belief came from.

• llms.txt. Google's generative AI optimization guide states that Google Search ignores these files and that maintaining one will "neither harm nor help" visibility or rankings. Ahrefs read the server logs for 137,210 domains and found 97% of published llms.txt files received zero requests during May 2026, with AI retrieval bots accounting for 1.1% of the requests that did arrive. It spread because it is cheap, it looks like robots.txt, and shipping one is legible as work.
• Structured data as a citation lever. Ahrefs ran the controlled version of this test in May 2026 — 1,885 pages given JSON-LD against matched controls — and found no uplift anywhere: −4.6% on AI Overviews, +2.4% on AI Mode, +2.2% on ChatGPT. Google says separately that no special schema.org markup is needed for AI features. The measurement is at Ahrefs' schema and AI citations test.
• "FAQ schema increases citations by 112%." The figure comes from a TechCognate study of roughly 1,000 Gemini queries whose authors write, in the study itself, that it is correlational and not causal. Two errors travel with it — a substituted surface and an upgraded causal claim — and the authors pre-empted the second in their own text.
• E-E-A-T checklists relabeled for AI. Pre-AI E-E-A-T — Experience, Expertise, Authoritativeness and Trust, the framework Google's external quality raters apply when scoring sample results — is not a ranking factor, and Google says so in writing. No operator documents author-level or credential-level signals of any kind. When Google published its generative AI optimization guide in May 2026, complete with a section on myths, the term did not appear in it. Silence in the one document written to answer this question is itself the finding.

What would settle any of these is the same in each case: a matched-pair test that isolates the variable, holds the visible text constant and publishes its method. Almost nobody publishes the study where nothing happened, which is worth remembering when reading a literature made entirely of positive results.

What genuinely follows from the architecture

Strip out everything undocumented and a short list survives, derived from how the system is built rather than from any Google statement about outcomes.

Ordinary ranking work still moves the candidate pool. Because AI features are grounded on the ordinary index, whatever gets a page crawled, indexed and ranked determines whether it can be selected at all. That is an argument from architecture, and the strongest available case for conventional work. It is not an argument that position one produces a citation.

Cover the subtopics, not only the head query. If the candidate pool is assembled per sub-query, a page that answers one narrow question well can enter an answer it does not rank for, and a page that ranks for the broad term can be passed over for sub-questions it never addresses. That follows directly from fan-out being documented. How many sub-queries, and which, does not.

Write passages that survive being read alone. A retrieved span is read without the rest of the page around it. A paragraph opening "as discussed above, it depends" is worthless out of context; one that names its subject in its first clause is not. That is observed rather than documented — no operator has confirmed it, and no published experiment isolates it on a live product.

Expect visibility, not sessions. Pew Research Center measured clicks on links inside AI summaries at 1% of visits in its March 2025 browsing data. Reporting a citation as traffic makes every downstream number wrong. One measured signal sits outside this frame and both sides of the argument leave it out: in the same Pew data, government sites made up 6% of AI summary sources against 2% of standard results — the only clean evidence anyone has produced that something trust-shaped operates in source selection at all.

What Search Console will and will not tell you

Since 3 June 2026 there is a generative AI performance report in Search Console, with data beginning 18 May 2026 and an initial rollout to a subset of site owners. What it omits is larger than what it contains. It reports impressions only, for AI Overviews and AI Mode combined, broken down by pages, countries, devices and dates. There is no query dimension, no click count, no clickthrough rate and no average position. Clicks from AI Overviews remain folded into the Web search type in the main Performance report, undifferentiated, as they always have been.

Two consequences follow. You cannot attribute a movement in that report to one surface, because two surfaces are merged into one figure, and Ahrefs measured only 13.7% citation overlap between them in December 2025. And you cannot compare generative AI impressions to Web impressions, because they are counted under different rules: Google confirmed in August 2024 that an AI Overview impression counts only when the link is scrolled or expanded into view, while ordinary organic impressions count on result-set generation. The ratio between the two is neither a clickthrough rate nor a visibility rate. Carolyn Shelby's summary is the right one: Google has given us a new diagnostic lens, not a new scoreboard.

Reproducibility is undercut from the other end too. Since 27 May 2026 a user's Preferred Sources selections are reflected inside AI Overviews and AI Mode, which makes part of the citation set user-configured by design.

How to read advice about AI Overviews

This page spends so long on evidence because the field's failure mode is not fabrication. It is honest measurement of a narrow thing, restated broadly by someone who benefits from the broad version. Three questions catch most of it.

Is the figure dated? A number quoted without a date here is not a fact, it is a fossil. The top-ten citation share had a seven-month half-life.

What is the denominator? Domain-share tables circulate as shares of all citations when they are shares of the top fifty sources; in May 2025 the top fifty domains accounted for 28.9% of all AI Overview mentions.

Was there a control group? Seer Interactive reported a 61% organic clickthrough decline on AI Overview queries in November 2025 and a 41% decline on queries without them over the same window. The differential is the finding; the headline carries only the first number.

Frequently asked questions